A new artificial intelligence algorithm can reliably screen chest X-rays for more than a dozen types of disease, and it does so in less time than it takes to read this sentence, according to a new study led by Stanford University researchers. The algorithm, dubbed CheXNeXt, is the first to simultaneously evaluate X-rays for a multitude of possible maladies and return results that are consistent with the readings of radiologists, the study says. Scientists trained the algorithm to detect 14 different pathologies: For 10 diseases, the algorithm performed just as well as radiologists; for three, it underperformed compared with radiologists; and for one, the algorithm outdid the experts. "Usually, we see AI algorithms that can detect a brain hemorrhage or a wrist fracture -- a very narrow scope for single-use cases," says associate professor of radiology Matthew Lungren. "But here we're talking about 14 different pathologies analyzed simultaneously, and it's all through one algorithm."